AI 编程助手——使用 Claude 和 GPT 构建类似 Cursor 的工具

import json
from openai import OpenAI
client = OpenAI(api_key="sk-kn-...", base_url="https://api.kunavo.com/v1")

# Code completion (autocomplete-as-you-type)
def complete(file_content: str, cursor_offset: int, file_path: str) -> str:
    before = file_content[:cursor_offset]
    after = file_content[cursor_offset:]
    resp = client.chat.completions.create(
        model="claude-haiku-4-5",   # FAST for IDE latency
        messages=[
            {"role": "system", "content": (
                "Complete the code at the cursor. Output ONLY the inserted "
                "text — no markdown, no explanation."
            )},
            {"role": "user", "content": (
                f"<file path=\"{file_path}\">\n{before}<CURSOR>{after}\n</file>"
            )},
        ],
        max_tokens=200,
        stop=["<CURSOR>", "</file>"],
    )
    return resp.choices[0].message.content

# Code review (heavier model). Claude enforces a json_schema
# response_format; json_object it does not.
REVIEW = {
    "type": "object",
    "properties": {
        "comments": {"type": "array", "items": {
            "type": "object",
            "properties": {"file": {"type": "string"},
                           "line": {"type": "integer"},
                           "comment": {"type": "string"}},
            "required": ["file", "line", "comment"],
            "additionalProperties": False,
        }},
        "verdict": {"type": "string", "enum": ["approve", "request_changes"]},
    },
    "required": ["comments", "verdict"],
    "additionalProperties": False,
}

def review(diff: str, conventions: str) -> dict:
    resp = client.chat.completions.create(
        model="claude-opus-5",
        messages=[
            {"role": "system", "content": [{
                "type": "text",
                "text": conventions,  # team style guide, security policy
                "cache_control": {"type": "ephemeral"},
            }]},
            {"role": "user", "content": f"Review this diff.\n\n{diff}"},
        ],
        response_format={"type": "json_schema",
                         "json_schema": {"name": "review", "schema": REVIEW}},
        max_tokens=2000,
    )
    return json.loads(resp.choices[0].message.content)